Data & AI Product Manager

TKO•Raleigh, CT

1d•$99,450 - $132,600•Remote

About The Position

TKO Group Holdings, Inc. is seeking a Data & AI Product Manager to own a portfolio of data products and capabilities supporting its sports and entertainment hospitality business, On Location. This role involves translating complex business needs into reusable data products, guiding engineering teams through delivery, and ensuring adoption and continuous improvement of launched capabilities. The position is part of the cross-TKO Data & AI Products & Services (DAPS) organization and collaborates closely with the On Location technology organization. The role will enable reporting and decision-making for major events and businesses, building reusable patterns across TKO.

Requirements

3+ years of experience in data product management, technical product management, analytics product management, data engineering, data science, analytics engineering, or a closely related field.
A strong technical foundation in at least one of the following: data engineering, software engineering, data science, analytics engineering, or data analysis - with the ability to reason credibly about the others.
Experience translating business problems into data models, analytical products, platform capabilities, integrations, APIs, pipelines, or AI-enabled workflows.
Working fluency with SQL and modern data concepts such as dimensional modeling, data quality, identity resolution, semantic layers, event instrumentation, warehouse/lakehouse architecture, APIs, and data lifecycle management.
Demonstrated ownership of products or complex initiatives from discovery through delivery, launch, adoption, and ongoing operation.
Strong execution and operating discipline: you keep commitments visible, follow up on dependencies, surface risks early, and close loops.
Excellent written and verbal communication, including the ability to explain technical tradeoffs and data limitations to senior business leaders.
Experience balancing multiple concurrent priorities in an environment with changing requirements, hard deadlines, and cross-functional dependencies.

Nice To Haves

A career path that began in engineering, data science, data analysis, analytics engineering, or another technical discipline before transitioning into product management.
Experience with Snowflake, Omni or another semantic/BI platform, Salesforce, Marketing Cloud or comparable activation systems, Amplitude/GA4, Census or similar reverse-ETL tools, and/or modern AI platforms.
Experience with customer 360, event or behavioral data, audience activation, attribution, lead scoring, marketing analytics, commissions, or commercial reporting.
Experience delivering products for live events, entertainment, sports, travel, hospitality, e-commerce, or another time-sensitive, customer-facing industry.
Experience working with governance, privacy, security, PII, data-sharing agreements, model risk, or responsible AI requirements.
Familiarity with Jira, agile delivery practices, product discovery, experimentation, and portfolio or product-operations cadences.
Genuine enthusiasm for entertainment, sports, live events, and the brands that make TKO unique.

Responsibilities

Own the product direction, roadmap, backlog, and lifecycle for On Location Base data products, including customer and transaction data, commercial reporting, marketing and audience activation, lead scoring, attribution, commissions, and operational analytics.
Oversee development of reusable data products on Snowflake, including dimensional models, curated data sets, semantic definitions, data interfaces, and governed self-service assets.
Partner with analytics and business teams to shape BI reporting and AI-enabled capabilities that solve real business problems and turn event-specific needs into reusable patterns where appropriate.
Act as a trusted advisor to stakeholders across product, pricing strategy, marketing, finance, sales, operations, guest/customer experience, and event leadership.
Shape unmet needs into opportunities with a clear user, decision, action, value hypothesis, success measure, dependencies, and stop/reconsider criteria.
Manage a visible multi-horizon portfolio, making tradeoffs across business value, urgency, risk, reuse, delivery confidence, capacity, and displaced work.
Convert product intent into clear Jira epics, stories, acceptance criteria, data contracts, measures, and decision records.
Partner day-to-day with TKO data engineering, analytics engineering, data science, platform, governance, security, and external delivery teams to move work from discovery through production.
Keep dependencies, milestones, risks, decisions, blockers, stakeholder commitments, launch readiness, adoption, and post-launch ownership visible.